Abstract
Road pavements need adequate maintenance to ensure that their conditions are kept in a good state throughout their lifespans. For this to be possible, authorities need efficient and effective databases in place, which have up to date and relevant road condition information. However, obtaining this information can be very difficult and costly and for smart city applications, it is vital. Currently, many authorities make maintenance decisions by assuming road conditions, which leads to poor maintenance plans and strategies. This study explores a pathway to obtain key information on a roadway utilizing drone imagery to replicate the roadway as a 3D model. The study validates this by using structure-from-motion techniques to replicate roads using drone imagery on a real road section. Using 3D models, flexible segmentation strategies are exploited to understand the road conditions and make assessments on the level of degradation of the road. The study presents a practical pipeline to do this, which can be implemented by different authorities, and one, which will provide the authorities with the key information they need. With this information, authorities can make more effective road maintenance decisions without the need for expensive workflows and exploiting smart monitoring of the road structures.
Highlights
Previous studies have focused on small sections of roads and have used the techniques at specific points of interest, whereas this study considers taking images in a continuous manner along the grade of the road establishing the possibility of modelling a full road section
Values are adequate given the level of details required and the size of typical pavement distresses [54]
digital elevation model (DEM), at different points of time over the years, for the road under analysis, the approach in this study available comparable DEMs, at different points of time over the years, for the road under analysis, provides for an analysis given limited data and provides the platform for the future development of the approach in this study provides for an analysis given limited data and provides the platform for the pipeline
Summary
Road agencies and authorities are facing tremendous difficulties when it comes to making critical maintenance decisions. Road authorities have to plan and implement appropriate pavement maintenance strategies that will allow roads to be kept in a good state. This is important because roads provide access and movement for people, goods and services within a city or community and with poor conditions, key social and economic activities would not be possible [1]. Constant reductions in road maintenance budgets [2] have limited the scope of these works which have made it more critical than ever to have low-cost systems in place that can provide data to enable good decision-making practices. The PMS is utilized as a support system for making decisions concerning planning road maintenance strategies
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